China’s economy grew by 4.8% year-on-year in the third quarter of 2025, marking its slowest expansion in a year and signaling that the world’s second-largest economy is entering a more complex phase of structural adjustment.

Although the growth rate aligned with analyst expectations, the underlying data reveal a deepening crisis in investment and confidence — particularly in the property sector, which continues to drag on overall output.

The weakness was most visible in fixed-asset investment, a crucial driver of China’s growth for decades. For the first nine months of the year, investment unexpectedly contracted by 0.5%, a rare decline and the first such contraction since 2020, when the pandemic paralyzed the economy. Analysts had anticipated a modest 0.1% increase, making the result significantly worse than expected.

The data highlight the fragility of China’s growth model, still heavily dependent on property and infrastructure, both of which are now faltering.

The country’s property sector remains the epicenter of the downturn. Property investment plunged 13.9% in the year through September, extending the 12.9% drop recorded through August. The sector’s prolonged slide reflects not just declining sales but also tighter financing, unfinished housing projects, and growing defaults among major developers.

The drop in fixed-asset investment is rare and alarming, CNBC quoted Zhiwei Zhang, president and chief economist at Pinpoint Asset Management, warning that fourth-quarter GDP growth faces downward pressure.

According to CNBC, Bruce Pang, adjunct associate professor at CUHK Business School, said the property slump could mark a lasting structural shift: “Weakness in real estate investment may persist for a longer period than previously anticipated. This could represent a structural restructuring, and it’s possible that investment will never return to its prior levels.”

Such a scenario would force Beijing to rethink its long-standing growth model, which has relied on heavy property development and infrastructure spending to sustain economic momentum.

Shifting Growth Drivers: From Property to Production

There were, however, pockets of strength in September. Industrial production grew 6.5%, exceeding expectations of 5% and rising from 5.2% the previous month. The resilience of manufacturing helped offset some of the drag from the property downturn.

Excluding real estate, fixed-asset investment rose 3% for the first three quarters, though that was slower than the 4.2% recorded as of August. Private sector investment outside property climbed 2.1%, down from 3% in August — another signal of waning business confidence.

“The weakness in investment spending, especially by the private sector, reflects a lack of confidence in the economy’s growth prospects as well as in government policies that could support growth,” said Eswar Prasad, professor of economics at Cornell University.

This hesitation among private investors underscores a growing challenge for Beijing: stimulating long-term, innovation-led investment without falling back on state-driven construction projects that have already led to excessive debt.

Consumer Spending Falters Despite Income Gains

Household consumption — the other critical pillar of domestic demand — remained tepid. Retail sales grew 3% in September from a year earlier, in line with forecasts but down from 3.4% in August. The slowdown suggests that consumers are tightening their wallets amid concerns about jobs and real estate wealth.

Sales of home appliances rose 3.3% in September, a sharp drop from the 25.3% surge recorded over the first three quarters, suggesting that the earlier consumer goods subsidy program is losing steam.

“I don’t think we could stimulate domestic demand without stabilizing the housing market first,” Dan Wang of Eurasia Group said Monday ahead of the data release on CNBC’s “Squawk Box Asia,” indicating the tight link between property confidence and consumer spending in China.

Official data show disposable income for urban residents rose 4.5% in the first nine months of the year, while rural income increased 6% after adjusting for inflation. Meanwhile, the urban unemployment rate edged down slightly to 5.2% in September, from 5.3% in August, providing a limited cushion for household sentiment.

Despite modest wage growth and employment gains, the combination of falling home prices, rising living costs, and subdued policy support has continued to sap consumer confidence — an issue Beijing has struggled to reverse.

Inflation and Policy Constraints

China’s price dynamics also point to persistent deflationary pressure. The core consumer price index (CPI), which excludes volatile food and energy costs, rose at its fastest pace since February 2024, but the headline CPI fell 0.3%, missing expectations.

This points to the dilemma facing policymakers: weak demand is keeping inflation below target, while financial risks tied to property and local government debt limit the scope for aggressive stimulus.

Earlier Monday, the People’s Bank of China kept its benchmark lending rates unchanged for the sixth straight month, maintaining the one-year loan prime rate at 3% and the five-year rate at 3.5%. The pause is seen as Beijing’s preference for targeted measures over broad rate cuts, as it seeks to stabilize the yuan and manage capital flows amid U.S. monetary tightening.

One bright spot remains China’s export sector, which showed continued resilience in September despite mounting geopolitical tensions with the United States. Manufacturing and high-value electronics exports have held up relatively well, supported by robust demand from Southeast Asia and Latin America.

Yet analysts warn that external demand may weaken if global growth slows further, especially with the U.S. economy showing signs of cooling and Europe battling persistent inflation.

The Push for Reform, Stability, and Control

China’s top leaders began a four-day policy meeting on Monday to chart economic priorities for the next five years. The central challenge, experts say, is how to maintain growth while steering the economy toward a new model less dependent on property and infrastructure.

Beijing has signaled a greater emphasis on domestic consumption and homegrown technology, particularly in sectors such as semiconductors, electric vehicles, and artificial intelligence. But analysts caution that this transition will take time and may not immediately compensate for the lost momentum in the property sector.

“China should step up its efforts in tech, but we also firmly believe the so-called old economy will remain the backbone of the economy for the foreseeable future,” said Ting Lu, Nomura’s Chief China Economist. “Beijing will have to clean up the property sector mess in 2026–2030 for several reasons.”

Lu noted that real estate remains second only to exports in contributing to GDP. At the same time, about half of Chinese household wealth is tied to property, and the sector still accounts for roughly 18% of local government revenue. He added that overinvestment in emerging industries such as electric vehicles has already become counterproductive, leading to overcapacity and inefficiencies.

However, the third-quarter data suggest that China’s economy is not in crisis, but at a crossroads. Growth remains respectable by global standards, yet its composition is shifting in ways that could redefine the country’s economic trajectory.

The property slump, weak private investment, and subdued consumer sentiment all point to a longer-term structural adjustment — one that will require a new balance between state guidance and market confidence.

Beijing’s next five-year plan will test whether the country can move beyond its property-dependent past toward a more innovation-driven future without triggering deeper financial instability.

The long-running debate over how to best achieve full vehicle autonomy—through cameras alone or a combination of multiple sensors—has resurfaced, with RoboSense founder Steven Qiu firmly taking a position against Tesla CEO Elon Musk’s “vision-only” approach.

Speaking to Business Insider on the sidelines of the FutureChina Global Forum in Singapore, Qiu argued that a vision-only system, such as the one Musk champions for Tesla’s Full Self-Driving (FSD) vehicles, cannot guarantee the safety required for higher levels of automation. Instead, he insists that the future of self-driving cars depends on a multi-sensor fusion model that integrates LiDAR, cameras, radar, and other sensing technologies.

“There’s been a lot of debate over whether a vision-only or multi-sensor approach is better when it comes to self-driving vehicles in the past 10 years or so,” Qiu said. “But by now, it is clear that everyone understands that a vision-only approach is not safe enough. There are a lot of corner cases that a vision-only system cannot account for.”

LiDAR—short for Light Detection and Ranging—is a laser-based sensing technology that measures distances by emitting beams of light and calculating the time it takes for the reflections to return. It builds a detailed 3D map of a vehicle’s surroundings, allowing for precise detection of obstacles, vehicles, and pedestrians—even in poor visibility conditions.

Qiu, whose company RoboSense has emerged as a global leader in automotive LiDAR production, explained that without LiDAR and other complementary sensors, autonomous driving systems would struggle to handle complex driving environments and unpredictable real-world conditions.

“Let’s say you are cruising on an expressway. If there is a white car that has stopped in front of you, it would be challenging for a vision-only system to tell if it’s a car or a white cloud in the sky,” he said. “Similarly, if you are driving toward a tunnel, the system may not be able to tell if there’s a black car driving ahead of you.”

According to Qiu, such “corner cases” make it impossible for camera-based systems to achieve higher levels of autonomy beyond Level 2 under SAE International’s standards. Level 2 systems, such as Tesla’s current FSD, require continuous human supervision. To reach Level 3 or Level 4—where vehicles can operate without driver input under certain conditions—manufacturers must integrate LiDAR and radar alongside cameras.

The SAE automation scale ranks vehicles from Level 1 (basic driver assistance, such as lane keeping or adaptive cruise control) to Level 5 (full autonomy in all conditions). Tesla’s FSD remains a Level 2 system, even as Musk repeatedly promises that full autonomy is on the horizon.

Qiu’s criticism comes amid a growing sentiment within the automotive industry that Tesla’s reliance on cameras alone—without radar or LiDAR—could limit its progress toward genuine self-driving capability. While Musk argues that artificial intelligence and vision-based systems will eventually outperform human perception, many engineers and automakers disagree.

RoboSense’s rise underscores this divergence in strategy. Founded in 2014, the company has become the world’s leading supplier of LiDAR sensors for passenger vehicles, according to Yole Group, a market research firm that published its findings in March 2024. RoboSense’s technology is already deployed in a wide range of vehicles and robotics applications—from Waymo’s autonomous taxis to household robot vacuums and even smartphone cameras.

Musk, however, has long maintained his opposition to LiDAR. During Tesla’s “Autonomy Day” event in April 2019, he called the technology “expensive and unnecessary,” insisting that visual recognition powered by neural networks would eventually be enough to safely drive a car.

“In cars, it’s friggin stupid. It’s expensive and unnecessary,” Musk said at the event. “Once you solve vision, it’s worthless. So you have expensive hardware that’s worthless on the car.”

He did acknowledge that SpaceX’s Dragon spacecraft uses LiDAR for docking maneuvers at the International Space Station, but he maintained that the technology had no place in consumer vehicles.

In recent years, Musk has reiterated that view, dismissing LiDAR as an inefficient cost burden. But the economics of LiDAR have changed drastically. Qiu pointed out that prices have fallen from around $70,000 per unit to just a few hundred dollars, while the technology’s performance has improved dramatically.

That cost reduction has made LiDAR systems more accessible to mass-market automakers. Ford, Volvo, Mercedes-Benz, and several Chinese electric vehicle makers have already incorporated LiDAR sensors into their semi-autonomous models.

Earlier this month, the U.S. National Highway Traffic Safety Administration (NHTSA) opened a sweeping federal investigation into potential safety defects in Tesla’s FSD system, after a growing number of crashes and traffic violations allegedly linked to the technology.

According to the NHTSA’s Office of Defects Investigation (ODI), the probe follows 44 reported incidents in which Tesla vehicles using FSD were said to have run red lights, veered into oncoming traffic, or committed other unsafe maneuvers that led to collisions, some resulting in injuries.

Ford CEO Jim Farley has openly contradicted Musk’s stance, calling LiDAR “mission critical” at the Aspen Ideas Festival in June.

“A reflection on the back of a truck or the sun in the camera’s eyes where the camera will be completely blinded—the LiDAR system will see exactly,” Farley said, highlighting how LiDAR provides a fail-safe layer of detection when cameras fail.

Similarly, Li Xiang, CEO of Chinese EV manufacturer Li Auto, emphasized that local driving conditions in China make LiDAR indispensable. At Li Auto’s “AI Talk” event last year, Li argued that Musk’s perspective overlooks the complexities of Chinese roads.

“If you drive in China at night, you will often see trucks with broken taillights, or even trucks without working taillights, just parked on the road,” he said. “Existing camera systems would not be able to detect these trucks from afar. I believe that if Musk were in China, and driving on various highways late in the night, he would choose to include LiDAR as well.”

Rivian CEO RJ Scaringe also made it clear earlier this month that the company’s approach to autonomous driving sharply differs from Tesla’s, emphasizing that LiDAR remains a critical and safer technology in building reliable self-driving systems.